Unlocking Opportunities for Gas Lift Well Surveillance - Building the Framework for Consolidated Data Capture and Processing

2021 ◽  
Author(s):  
Rachelle Christine Cornwall ◽  
Daniel Dima Shkorin ◽  
Rodrigo Alberto Guzman ◽  
Jalal Rojdi El-Majzoub ◽  
Mahrous Sadek El-Sedawy ◽  
...  
Keyword(s):  
Material Selection ◽  
Scale Up ◽  
Gas Analysis ◽  
Well Performance ◽  
Opportunity Identification ◽  
Full Data ◽  
Traditional Methods ◽  
Full Field ◽  
Flow Stabilization ◽  
Gas Lift

Abstract Gas lift operations are highly dependent on data quality and team competence to operate the asset efficiently. Traditional methods for gas lift well surveillance and diagnostics rely on wireline services, a method with growing constraints to adapt to constantly evolving well and operational challenges. The Well Intervention-less Tracer Surveillance System (WITSS) provides a cost effective, comprehensive approach to well surveillance without the reliance on tools entering the well. This results in reduced HSE risks and no associated deferred production. This paper describes a pilot implementation to evaluate the adequacy and accuracy of this technology in the context of ADNOC Onshore gas lift producers. The objective is to evaluate its performance against conventional method data sets and assess the reproducibility of data where no reference existed. The 10 well pilot included both accessible and obstructed wells. Data from the custom designed modular portable kit used for executing the surveillance activities, was analyzed and compared against conventional flowing gradient surveys with full data consumption in well models for comprehensive nodal analysis and opportunity identification. For this pilot, ten wells were surveyed twice using the WITSS method. Results were compared to traditional methods acquired through wireline surveys for accessible wells, and against established multi-phase flow correlations for obstructed wells. The pilot confirmed the WITSS method is as accurate as conventional gauge measurements in mapping pressure and temperature profiles in gas lifted wells. The WITSS method provided additional insight on accurate gas consumption based on the assessment of total gas lift utilization per well and allowed comprehensive model calibration and well performance definition. It also identified potential integrity issues via identification of primary injection at designed stations and secondary unwanted injection sites. Continuous compositional gas analysis of both injected and produced gas streams provided additional verification for analyzing gas lift injection performance. It also highlighted a change in fluid compositional analysis opening discussions for material selection review of the assets. Production uplift identified from 50% of wells was compliant with the reservoir management strategy. The value proposals of flow stabilization through gas lift valve re-calibrations and replacements, adjustment of injection flow rate and further controls on injection pressure management are under process for implementation. Full field scale up scenario is under preparation.

Artificial Intelligence Assisted Well Portfolio Optimization - An Automated Reservoir Management Advisory System to Maximize the Asset Value - Case Study from ADNOC Onshore

2021 ◽  
Author(s):  
Subba Ramarao Rachapudi Venkata ◽  
Nagaraju Reddicharla ◽  
Shamma Saeed Alshehhi ◽  
Indra Utama ◽  
Saber Mubarak Al Nuimi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Hybrid Approach ◽  
Simulation Models ◽  
Production Optimization ◽  
Added Value ◽  
Risk Scores ◽  
Well Performance ◽  
Field Development ◽  
Advisory System ◽  
Gas Lift

Abstract Matured hydrocarbon fields are continuously deteriorating and selection of well interventions turn into critical task with an objective of achieving higher business value. Time consuming simulation models and classical decision-making approach making it difficult to rapidly identify the best underperforming, potential rig and rig-less candidates. Therefore, the objective of this paper is to demonstrate the automated solution with data driven machine learning (ML) & AI assisted workflows to prioritize the intervention opportunities that can deliver higher sustainable oil rate and profitability. The solution consists of establishing a customized database using inputs from various sources including production & completion data, flat files and simulation models. Automation of Data gathering along with technical and economical calculations were implemented to overcome the repetitive and less added value tasks. Second layer of solution includes configuration of tailor-made workflows to conduct the analysis of well performance, logs, output from simulation models (static reservoir model, well models) along with historical events. Further these workflows were combination of current best practices of an integrated assessment of subsurface opportunities through analytical computations along with machine learning driven techniques for ranking the well intervention opportunities with consideration of complexity in implementation. The automated process outcome is a comprehensive list of future well intervention candidates like well conversion to gas lift, water shutoff, stimulation and nitrogen kick-off opportunities. The opportunity ranking is completed with AI assisted supported scoring system that takes input from technical, financial and implementation risk scores. In addition, intuitive dashboards are built and tailored with the involvement of management and engineering departments to track the opportunity maturation process. The advisory system has been implemented and tested in a giant mature field with over 300 wells. The solution identified more techno-economical feasible opportunities within hours instead of weeks or months with reduced risk of failure resulting into an improved economic success rate. The first set of opportunities under implementation and expected a gain of 2.5MM$ with in first one year and expected to have reoccurring gains in subsequent years. The ranked opportunities are incorporated into the business plan, RMP plans and drilling & workover schedule in accordance to field development targets. This advisory system helps in maximizing the profitability and minimizing CAPEX and OPEX. This further maximizes utilization of production optimization models by 30%. Currently the system was implemented in one of ADNOC Onshore field and expected to be scaled to other fields based on consistent value creation. A hybrid approach of physics and machine learning based solution led to the development of automated workflows to identify and rank the inactive strings, well conversion to gas lift candidates & underperforming candidates resulting into successful cost optimization and production gain.

An Expert Software System has Accomplished Full Implementation of Well Integrity Management System WIMS Resulting to Excellent Safety and Production Sustainability for Critical Sour HPHT Field in Offshore Madura Strait, Indonesia

2021 ◽  
Author(s):  
Fianti Ramadhani ◽  
Syaiful Nurdin ◽  
Michael Olu Etuhoko ◽  
Yang Zhi ◽  
Sugeng Mulyono ◽  
...  
Keyword(s):  
Management System ◽  
Material Selection ◽  
International Standards ◽  
Software System ◽  
Well Performance ◽  
Integrity Test ◽  
Well Integrity ◽  
High Pressure High Temperature ◽  
Integrity Management ◽  
Productive Assets

Abstract Four high-pressure-high temperature (HPHT) and sour gas wells are currently operating at Madura offshore as the only productive assets for Husky-CNOOC Madura Limited (HCML). Each well performance is very crucial to fulfill the demand of the gas customers in East Java, Indonesia. Since starting production in 2017, the wells experienced two main well integrity challenges, high annulus pressure and wellhead growth. Both challenges are very dependent to the well flow rate and the flow duration. A continuous operation monitoring is highly required in order to keep the wells operating safely. To overcome the challenges, HCML established a Well Integrity Management System (WIMS) document that approached several international standards as its basis. As company grows, development plan challenged the WIMS to perform faster and more efficient as compared to the existing manual system. From there, the journey of WIMS digitalization began. The journey started with the alignment of the existing WIMS document to the ISO-16530-1 at Operational Phase with more stringent boundary to operate the wells safely. The alignment covers, but not limited to the organizational structure, well barriers and criteria, monitoring and surveillance, annulus pressure management, and maintenance. The document also covered risk assessment and management of well integrity failure, which was the backbone of the WIMS digitalization. The current digital solutions allow production data to be accessed and retrieved directly from the system for analysis purposes. It compares the recorded data with pre-determined rules and parameters set in the system. It triggers a notification to the responsible personnel to perform the required action should any anomaly occurs. It also can send a reminder to users to schedule and complete a well Integrity test to ensure that a well is always in compliance with the WIMS. All test reports and documentation are stored in the system as preparation for any future audit. A key requirement of the expert software system was access to future developments that can offer enhanced functionality of the well integrity platform through additional near time capabilities such as predictive erosion and corrosion for downhole flow wetted components. This is being developed to enhance workover scheduling for existing wells and material selection for new wells and is planned to update automatically critical well integrity criteria such as tubing burst, collapse and MAASP.

scholarly journals IMPACT OF GAS LIFT INJECTION RATE ON OIL PRODUCTION RATE

2021 ◽  
pp. 76-94
Author(s):  
Dr. Mohamed A. GH. Abdalsadig
Keyword(s):  
Real Time ◽  
Energy Demand ◽  
Oil And Gas ◽  
Injection Pressure ◽  
Production Operation ◽  
Well Performance ◽  
Time Data ◽  
Daily Work ◽  
Wellhead Pressure ◽  
Gas Lift

As worldwide energy demand continues to grow, oil and gas fields have spent hundreds of billions of dollars to build the substructures of smart fields. Management of smart fields requires integrating knowledge and methods in order to automatically and autonomously handle a great frequency of real-time information streams gathered from those wells. Furthermore, oil businesses movement towards enhancing everyday production skills to meet global energy demands signifies the importance of adapting to the latest smart tools that assist them in running their daily work. A laboratory experiment was carried out to evaluate gas lift wells performance under realistic operations in determining reservoir pressure, production operation point, injection gas pressure, port size, and the influence of injection pressure on well performance. Lab VIEW software was used to determine gas passage through the Smart Gas Lift valve (SGL) for the real-time data gathering. The results showed that the wellhead pressure has a large influence on the gas lift performance and showed that the utilized smart gas lift valve can be used to enhanced gas Lift performance by regulating gas injection from down hole.

Study on Sizes Optimization and Material Selection of Casing Material in Gas-Lift Well under Existence of CO2 Corrosion

2013 ◽  
Vol 700 ◽  
pp. 59-62
Author(s):  
Ling Feng Li
Keyword(s):  
Material Selection ◽  
Oil Wells ◽  
Working Environments ◽  
Gas Lift ◽  
Selection Of

Some oil wells have adverse working environments, material selection and sizes optimization of casing material for gas-lift well under existence of CO2corrosion are very important. This paper presents the development background, sizes optimization of casing material for gas-lift well, effect of CO2on material of casing, casing material selection. By testing, the study above has a strong practicality and can be suitable for the well condition of on-the-spot application.

scholarly journals A Newly Designed Automatically Controlled, Sterilizable Flat Panel Photobioreactor for Axenic Algae Culture

2021 ◽  
Vol 9 ◽  
Author(s):  
Tobias Fuchs ◽  
Nathanael D. Arnold ◽  
Daniel Garbe ◽  
Simon Deimel ◽  
Jan Lorenzen ◽  
...  
Keyword(s):  
Global Climate ◽  
Scale Up ◽  
Food Additives ◽  
Academic Research ◽  
Laboratory Scale ◽  
Flat Panel ◽  
Engineering Technology ◽  
Control Technologies ◽  
Industrial Standards ◽  
Gas Lift

In context of the global climate change, microalgae processes are gaining momentum as a biotechnological tool for direct fixation and valorization of greenhouse gases. Algae have the metabolic capacity to photosynthetically convert CO2 into high value products, such as food additives, under economic boundary conditions. High cost, commercial flat panel gas-lift bioreactors for microalgae cultivation at laboratory scale provide either small volumes or no sterile operation, which limits academic research. This brief report presents initial data for a new type of sterile operating flat panel gas-lift bioreactor with a unique asymmetrical U-shape. It utilizes automatable process control technologies that adhere to industrial standards to enhance data reproducibility and aid industrial scale up. The practicability was demonstrated using a Chlorella sorokiniana cultivation, which showed the typical growth behavior. Due to the sophisticated implemented control engineering technology, pivotal parameters as pH and temperature can be determined within a range of ±0.1 units, which was confirmed experimentally. The new flat panel gas-lift photobioreactor presented in this brief report fills the technology gap at laboratory scale with an autoclavable volume of 7.2 L. Moreover, it is easy to rebuild by means of the hereby provided blueprint, while exhibiting a six-fold cost reduction compared to commercially available flat panel photobioreactors.

scholarly journals EPS Conceptual Design for GoM Deepwater Fields

2010 ◽  
Author(s):  
Michael Choi ◽  
Andrew Kilner ◽  
Hayden Marcollo ◽  
Tim Withall ◽  
Chris Carra ◽  
...  
Keyword(s):  
Conceptual Design ◽  
Oil And Gas ◽  
Cost Effective ◽  
Test System ◽  
Well Test ◽  
Well Performance ◽  
Compressed Natural Gas ◽  
Full Field ◽  
Field Development ◽  
Early Production

To avoid making billion dollar mistakes, operators with discoveries in deepwater (∼3,000m) Gulf of Mexico (GoM) need dependable well performance, reservoir response and fluid data to guide full-field development decisions. Recognizing this need, the DeepStar consortium developed a conceptual design for an Early Production System (EPS) that will serve as a mobile well test system that is safe, environmentally friendly and cost-effective. The EPS is a dynamically positioned (DP) Floating, Production, Storage and Offloading (FPSO) vessel with a bundled top tensioned riser having quick emergency disconnect capability. Both oil and gas are processed onboard and exported by shuttle tankers to local markets. Oil is stored and offloaded using standard FPSO techniques, while the gas is exported as Compressed Natural Gas (CNG). This paper summarizes the technologies, regulatory acceptance, and business model that will make the DeepStar EPS a reality. Paper published with permission.

Augmented AI Framework for Well Performance Prediction and Opportunity Identification in Unconventional Reservoirs

2020 ◽  
Author(s):  
Hamed Darabi ◽  
Xiang Zhai ◽  
Amir Kianinejad ◽  
Zheren Ma ◽  
David Castineira ◽  
...  
Keyword(s):  
Performance Prediction ◽  
Unconventional Reservoirs ◽  
Well Performance ◽  
Opportunity Identification

Optimization of Tracer Injection Schemes for Improved History Matching

2021 ◽  
Author(s):  
Hsieh Chen ◽  
Hooisweng Ow ◽  
Martin E Poitzsch
Keyword(s):  
History Matching ◽  
Large Scale ◽  
Reservoir Characterization ◽  
Statistical Significance ◽  
Scale Up ◽  
Production Optimization ◽  
Tracer Injection ◽  
Full Field ◽  
Multiple Data ◽  
Mean Square Errors

Abstract Interwell tracers are powerful reservoir surveillance tools that provide direct reservoir flow paths and dynamics, which, when integrated with near real-time production optimization, can greatly improve recovery factor, and return on investment, the so-called "Advanced Tracers System" (ATS). Applying full field ATS is attractive for resource-holders, especially for those with large waterflood operations. However, to scale up ATS to cover large fields with potentially tens to hundreds of injectors and producers, the required unique tracer variations ("barcodes") and materials and associated analysis may increase rapidly. Here, we explore different tracer injection schemes that can acquire the most information while using reduced numbers of tracers, thereby controlling costs in field operations. We tested the designs of various modified tracer injection schemes with reservoir simulations. Numerical experiments were performed on synthetic fields with multiple injector and producer wells in waterflooding patterns. Two tracer injection schemes were considered: In Scheme 1, all injectors were injected with unique tracers representing the most information-rich case. In Scheme 2, some injectors were injected with the same tracers ("recycling" the same barcodes), and some injectors received no tracer injection ("null" barcodes). Production and tracer breakthrough data was collected for history matching after waterflooding simulations on the synthetic fields. The ensemble smoother with multiple data assimilation with tracers algorithm was used for history matching. We calculated the root-mean-square errors (RMSE) between the reference data and the history matched production simulation data. To improve the statistics, 20 independent testing reference synthetic fields were constructed by randomizing the number and locations of high permeability zones crossing different injectors and producers. In all cases, the history matching algorithms largely reduced the RMSE thereby enhancing reservoir characterization. Analyzing the statistical significance with p-values among testing cases, first, as expected, the data mismatch is highly significantly lower after history matching than before history matching (p < 0.001). Second, the data mismatch is even lower when history matching with tracers (both in Scheme 1 and 2) than without tracers (p < 0.05), demonstrating clearly that tracers can provide extra information for the reservoir dynamics. Finally, and most importantly, history matching with tracers in Scheme 1 or in Scheme 2 result in statistically the same data mismatch (p > 0.05), indicating the cost-saving "recycling" and "null" tracer barcodes can provide equally competent reservoir information. To the best of our knowledge, this is the first study that evaluated the history matching qualities deriving from different tracer injection schemes. We showed that through optimal designs of the tracer injections, we can acquire very similar information with reduced tracer materials and barcodes, thus reducing costs and field operational complexities. We believe this study facilitates the deployment of large-scale reservoir monitoring and optimization campaigns using tracers such as ATS.

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